AIMC Topic: Epigenesis, Genetic

Clear Filters Showing 151 to 160 of 168 articles

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.

Briefings in bioinformatics
DNA N4-methylcytosine (4mC) is an important epigenetic modification that plays a vital role in regulating DNA replication and expression. However, it is challenging to detect 4mC sites through experimental methods, which are time-consuming and costly...

Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning.

Briefings in bioinformatics
DNA N4-methylcytosine (4mC) modification represents a novel epigenetic regulation. It involves in various cellular processes, including DNA replication, cell cycle and gene expression, among others. In addition to experimental identification of 4mC s...

Deep learning for biological age estimation.

Briefings in bioinformatics
Modern machine learning techniques (such as deep learning) offer immense opportunities in the field of human biological aging research. Aging is a complex process, experienced by all living organisms. While traditional machine learning and data minin...

A machine learning-based framework for modeling transcription elongation.

Proceedings of the National Academy of Sciences of the United States of America
RNA polymerase II (Pol II) generally pauses at certain positions along gene bodies, thereby interrupting the transcription elongation process, which is often coupled with various important biological functions, such as precursor mRNA splicing and gen...

Artificial Intelligence for Epigenetics: Towards Personalized Medicine.

Current medicinal chemistry
Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function, not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mec...

Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data.

Bioinformatics (Oxford, England)
MOTIVATION: Predictive models of DNA chromatin profile (i.e. epigenetic state), such as transcription factor binding, are essential for understanding regulatory processes and developing gene therapies. It is known that the 3D genome, or spatial struc...

Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning-based neural network.

GigaScience
BACKGROUND: Gene expression plays a key intermediate role in linking molecular features at the DNA level and phenotype. However, owing to various limitations in experiments, the RNA-seq data are missing in many samples while there exist high-quality ...

DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.

Bioinformatics (Oxford, England)
MOTIVATION: DNA N4-methylcytosine (4mC) is a crucial epigenetic modification. However, the knowledge about its biological functions is limited. Effective and accurate identification of 4mC sites will be helpful to reveal its biological functions and ...

Functional interpretation of genetic variants using deep learning predicts impact on chromatin accessibility and histone modification.

Nucleic acids research
Identifying functional variants underlying disease risk and adoption of personalized medicine are currently limited by the challenge of interpreting the functional consequences of genetic variants. Predicting the functional effects of disease-associa...

WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach.

Nucleic acids research
N 6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotes, and plays a pivotal role in various biological processes, such as splicing, RNA degradation and RNA-protein interaction. We report here a prediction fram...